Breast cancer is a heterogeneous disease with diverse outcomes and response to therapy. Basal-like breast cancers (BBC), which account for 15-20% of all breast cancer, share a distinct pattern of gene expression that includes elevated basal cytokeratins and DNA replication factors. On the other hand, basal-like breast cancers are heterogeneous among themselves with regard to metastatic potential and genetic alterations. Therefore, the driving forces for the growth and poor prognosis of BBC must be identified before therapeutic strategies with a high chance of success can be developed. The long-term objective of this program is to define the oncogene and tumor suppressor pathways at work in different forms of BBC to better predict their clinical behavior and to develop approaches for attacking these tumors. We and others have established that, as a class, BBC frequently deregulate MYC, p53, PTEN, BRCA1, and we have preliminary data showing the same for HAUSP. How or when these alterations cooperate in any specific BBC development is not understood. Each of the projects in the newly revised application is focused on defining the pathways that cause basal-like cancer and then discerning the basis for their contribution to the tumor phenotype. Project 1 will seek to understand the role of PTEN and other PI3K pathway regulators in BBC. Project 2 will determine the function of HAUSP in the regulation of PTEN ubiquitination and BBC tumor suppression. Projects will focus on the ubiquitin-ligase function of BRCA1 in hereditary BBC tumor suppression and the development of a more accurate model of the disease. Project 4 will study the ability of MYC to induce DNA replication stress and mechanisms of escape to produce DNA replication through the inactivation of tumor suppressors PTEN, p53 and BRCA1. The projects will be supported by cores for administration/analysis and breast pathology. The program relies on the integration of different expertise in the areas of molecular pathology, mammary cell engineering, biochemistry, genetics, systems biology, bioinformatics, biostatistics, and cell function analysis. Ultimately, we hope to better understand the mechanisms through which the network of altered pathways in basal-like breast cancer drives tumor growth in order to better predict tumor phenotype, i.e., metastasis, and develop strategies for therapy.